Scale-Space and Edge Detection Using Anisotropic Diffusion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Edge Detection and Ridge Detection with Automatic Scale Selection
International Journal of Computer Vision
A rotation invariant printed Chinese character recognition system
Pattern Recognition Letters
Digital Image Processing (3rd Edition)
Digital Image Processing (3rd Edition)
Mean shift blob tracking with kernel histogram filtering and hypothesis testing
Pattern Recognition Letters
Review article: Edge and line oriented contour detection: State of the art
Image and Vision Computing
An algorithm for automatic curve detection
Computational Statistics & Data Analysis
Object detection with feature stability over scale space
Journal of Visual Communication and Image Representation
A study and analysis of digital image processing and recognition algorithms
International Journal of Computer Applications in Technology
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Spatial image filtering is a method by which an image can be enhanced. The method involves computing correlation of a mask and input image to produce desired image. This requires a number of computations consisting of addition and division operations. Such operations are repeated multiple times for common areas of overlapping masks as we shift the mask over consecutive pixels. As a result, there is a significant number of redundant operations that slows down the spatial filtering process. In this paper, we propose a new method to eliminate redundant operations and we apply it to volumetric MRI images using mean filter. We analyse the complexity of the proposed method and compare its processing speed to that of the conventional implementation of the mean filter. Our method shows up to one order of magnitude improvement in processing speed over the conventional method especially on 3D images with large filter masks.